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AleRax: A tool for gene and species tree co-estimation and reconciliation under a probabilistic model of gene duplication, transfer, and loss

View ORCID ProfileBenoit Morel, Tom A. Williams, Alexandros Stamatakis, Gergely J. Szöllősi
doi: https://doi.org/10.1101/2023.10.06.561091
Benoit Morel
1Computational Molecular Evolution group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
2Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
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  • ORCID record for Benoit Morel
  • For correspondence: benoit.morel@h-its.org
Tom A. Williams
3School of Biological Sciences, University of Bristol, Bristol, UK
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Alexandros Stamatakis
4Biodiversity Computing Group, Institute of Computer Science, Foundation for Research and Technology - Hellas
1Computational Molecular Evolution group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
2Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
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Gergely J. Szöllősi
5ELTE-MTA “Lendület” Evolutionary Genomics Research Group, Pázmány P. stny. 1A., H-1117 Budapest, Hungary
6Institute of Evolution, Centre for Ecological Research, Konkoly-Thege M. út 29-33. H-1121 Budapest, Hungary
7Model-Based Evolutionary Genomics Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
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ABSTRACT

Motivation Genomes are a rich source of information on the pattern and process of evolution across biological scales. How best to make use of that information is an active area of research in phylogenetics. Ideally, phylogenetic methods should not only model substitutions along gene trees, which explain differences between homologous gene sequences, but also the processes that generate the gene trees themselves along a shared species tree. To conduct accurate inferences, one needs to account for uncertainty at both levels, that is, in gene trees estimated from inherently short sequences and in their diverse evolutionary histories along a shared species tree.

Results We present AleRax, a software that can infer reconciled gene trees together with a shared species tree using a simple, yet powerful, probabilistic model of gene duplication, transfer, and loss. A key feature of AleRax is its ability to account for uncertainty in the gene tree and its reconciliation by using an efficient approximation to calculate the joint phylogenetic-reconciliation likelihood and sample reconciled gene trees accordingly. Simulations and analyses of empirical data show that AleRax is one order of magnitude faster than competing gene tree inference tools while attaining the same accuracy. It is consistently more robust than species tree inference methods such as SpeciesRax and ASTRAL-Pro 2 under gene tree uncertainty. Finally, AleRax can process multiple gene families in parallel thereby allowing users to compare competing phylogenetic hypotheses and estimate model parameters, such as DTL probabilities for genome-scale datasets with hundreds of taxa

Availability and Implementation GNU GPL at https://github.com/BenoitMorel/AleRax and data are made available at https://cme.h-its.org/exelixis/material/alerax_data.tar.gz.

Contact Benoit.Morel{at}h-its.org

Supplementary information Supplementary material is available.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Author list updated, title updated

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted October 08, 2023.
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AleRax: A tool for gene and species tree co-estimation and reconciliation under a probabilistic model of gene duplication, transfer, and loss
Benoit Morel, Tom A. Williams, Alexandros Stamatakis, Gergely J. Szöllősi
bioRxiv 2023.10.06.561091; doi: https://doi.org/10.1101/2023.10.06.561091
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AleRax: A tool for gene and species tree co-estimation and reconciliation under a probabilistic model of gene duplication, transfer, and loss
Benoit Morel, Tom A. Williams, Alexandros Stamatakis, Gergely J. Szöllősi
bioRxiv 2023.10.06.561091; doi: https://doi.org/10.1101/2023.10.06.561091

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